Modelling conformational state dynamics and its role on infection for SARS-CoV-2 Spike protein variants
| Autor: | Rafael Najmanovich, Olivier Mailhot, Natália Teruel |
|---|---|
| Rok vydání: | 2021 |
| Předmět: |
RNA viruses
Viral Diseases Coronaviruses Epidemiology Protein Conformation Mutant medicine.disease_cause Biochemistry Medical Conditions 0302 clinical medicine Protein structure Amino Acids Biology (General) Pathology and laboratory medicine 0303 health sciences Mutation Ecology Transition (genetics) Organic Compounds Physics Microbial Mutation Dynamics (mechanics) Classical Mechanics Medical microbiology 3. Good health Chemistry Infectious Diseases Computational Theory and Mathematics Modeling and Simulation Viruses Physical Sciences Spike Glycoprotein Coronavirus Spike (software development) SARS CoV 2 Pathogens Research Article SARS coronavirus Proline QH301-705.5 In silico Severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2) Computational biology Biology Markov model Microbiology Vibration 03 medical and health sciences Cellular and Molecular Neuroscience Viral entry Genetics medicine Point Mutation Humans Pandemics Molecular Biology Ecology Evolution Behavior and Systematics 030304 developmental biology Medicine and health sciences Biology and life sciences SARS-CoV-2 Point mutation Organic Chemistry Organisms Viral pathogens Chemical Compounds Wild type Proteins COVID-19 Covid 19 Cyclic Amino Acids Microbial pathogens 030217 neurology & neurosurgery |
| Zdroj: | PLoS Computational Biology, Vol 17, Iss 8, p e1009286 (2021) PLoS Computational Biology |
| ISSN: | 1553-7358 |
| Popis: | The SARS-CoV-2 Spike protein needs to be in an open-state conformation to interact with ACE2 to initiate viral entry. We utilise coarse-grained normal mode analysis to model the dynamics of Spike and calculate transition probabilities between states for 17081 variants including experimentally observed variants. Our results correctly model an increase in open-state occupancy for the more infectious D614G via an increase in flexibility of the closed-state and decrease of flexibility of the open-state. We predict the same effect for several mutations on glycine residues (404, 416, 504, 252) as well as residues K417, D467 and N501, including the N501Y mutation recently observed within the B.1.1.7, 501.V2 and P1 strains. This is, to our knowledge, the first use of normal mode analysis to model conformational state transitions and the effect of mutations on such transitions. The specific mutations of Spike identified here may guide future studies to increase our understanding of SARS-CoV-2 infection mechanisms and guide public health in their surveillance efforts. Author summary The present work explores the molecular mechanisms underlying and potentially helping new strains of SARS-CoV-2 to gain an evolutionary advantage during the ongoing COVID-19 pandemics. We show how a computational method called normal mode analysis that treats protein dynamics in a simplified manner is capable to predict the higher propensity of the Spike protein to be in the open state in which it is capable to interact with the human ACE2 receptor and thus facilitate cell entry. Because the simulation of the simplified computational model is relatively less demanding on resources than alternative methods, we were able to simulate over 17000 mutations in the SARS-CoV-2 Spike protein to identify multiple mutations that if they were to appear as the virus continues to evolve, could confer an evolutionary advantage. As a matter of fact, our predictions foresaw the emergence of particular mutations such as N501Y that appeared in several variants of concern. Our results can inform public health regarding new variants and serves as a proof of concept for the application of normal mode analysis to study the effect of mutations on both, protein dynamics and conformational transitions in a high-throughput manner. |
| Databáze: | OpenAIRE |
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